Search Results (28)

In the single-depot multi-traveling salesman problem, traditional depot location methods often overlook task balance among traveling salesmen, leading to excessive load on certain units and compromising overall operational efficiency. To address this issue, this paper proposes an optimized depot location method based on clustering and multi-task balancing. The core contribution lies in the design of a multi-weight adaptive depot optimization method. This approach clusters city nodes into multiple groups through cluster analysis and dynamically synthesizes direction vectors using information such as the number of samples within each cluster and the convex perimeter. It iteratively optimizes depot locations, minimizing the total path length while enhancing workload balance across all traveling salesman routes. Additionally, a “divide-and-conquer” strategy decomposes the complex MTSP into multiple parallel TSP subproblems, which are then efficiently solved using Or-Tools. A comprehensive evaluation framework is introduced, incorporating Total-Sum distance, Min-Max distance, Workload Balance, Cluster separability, Robustness, and Running time. Experimental results on the TSPLIB standard dataset demonstrate that the proposed method exhibits significant advantages over various traditional clustering algorithms in both route optimization and route balancing, validating its effectiveness and practicality. The method’s robust performance provides a reliable solution for real-world applications such as logistics distribution, further highlighting its practical value. Experimental results show that the proposed method reduces the total travel distance and improves workload balance on multiple TSPLIB instances compared with conventional depot selection baselines. Full article

Meningiomas are the most common central nervous system tumour and are associated with significant morbidity. Mounting evidence implicates the role of exogenous hormones in meningioma development and growth. This has led to increasing pressure on healthcare professionals to understand the risk profile of different hormonal compounds with regards to meningioma incidence and growth. This is particularly relevant when managing patients with pre-existing meningioma tumours or with one or more risk factors for meningioma formation. The aim of this review was to summarise existing evidence from clinical studies (cohort and case–control) concerning the risk of meningioma associated with different types of exogenous hormones and the associated meningioma characteristics. The literature review identified over 30 cohort and case–control studies published between 2003 and 2026. Studies demonstrated a mixed risk profile of broadly defined hormonal replacement therapy and hormonal contraceptives; however, many of these studies did not capture specific information about duration, dose or medication type. Risk associated with synthetic progestin-containing compounds such as depot medroxyprogesterone and desogestrel contraceptives was higher and related to duration of use. Highly potent synthetic progestins including cyproterone acetate (CPA) carried the strongest risk profile and showed a strong association with multiple meningiomas and anterior/middle skull base location. In conclusion, there is strong evidence for a link between meningioma incidence and highly potent synthetic progestins such as CPA, but further evidence is needed regarding menopausal hormone therapy and broadly defined oral contraceptives, as well as the doses and durations that are associated with clinically relevant risk. There is a space for translational research in this area to better understand the molecular basis underlying the relationship between hormones and meningioma growth. Full article

Unmanned Aerial Vehicles (UAVs) increasingly operate in missions requiring the simultaneous satisfaction of multiple objectives: reaching task locations, performing the correct service, and preserving sufficient onboard energy for continuous operation. Mission efficiency depends not only on task completion but also on managing the trade-off between service duration and battery recharging. This work proposes a Double Deep Q-Network (DDQN) policy for energy-aware UAV navigation on graph maps. The UAV must first collect the appropriate servicing tool from a depot node and then deliver it to the active failure node. At the same time, it autonomously decides when to interrupt the mission for recharging so as to ensure sufficient battery reserve throughout continuous operations, while minimizing task-servicing duration. The key contribution is an energy-aware reward based on a Dynamic Battery Threshold (DBT) computed from graph shortest-path distances to the nearest charging station, enabling a topology-aware recharge policy that is safer yet less conservative than a per-map tuned safety margin. Extensive Monte Carlo tests on increasingly complex graphs show that the proposed policy achieves a 100% task completion rate with always sufficient final battery to reach a charging node from the task node, while degrading less with map complexity and exhibiting greater robustness to stochastic battery dynamics than a pseudo-optimal baseline. Full article

Train-induced ground vibrations can propagate into pile foundations, potentially causing undesirable vibration in nearby buildings, laboratories housing vibration-sensitive equipment, and manufacturing facilities for high-precision processes. This paper presents an innovative method for predicting building vibration from free-field ground vibration measurements at locations away from the tracks during train pass-bys. The proposed method accounts for site-specific soil profiles and train-soil-pile-structure interactions and is implemented in four steps. In Step 1, train-induced vibration transmission into the ground is estimated using an axisymmetric finite element model that simulates wave propagation through layered soils from the tracks to free-field ground locations. Step 2 estimates free pile head vibration using a three-dimensional finite-element model that captures the ground-borne transmission of track inputs through soil layers to the pile. Step 3 estimates vibration at the junction of the pile head and depot column base using a finite-element model to estimate the pile head impedance and an analytical impedance model for the depot structures supported by the pile. In Step 4, estimates of column-base vibration that transmits into over-track buildings are compared to measured column-base vibration levels obtained during train pass-bys. The method was applied at a metro depot in China, where tracks were in close proximity to columns supporting over-track buildings. Ground and column base vibration levels were measured during multiple train pass-bys. The estimated vibration levels at the base of depot columns closely agreed with the measured vibration levels at the columns during six-car train pass-bys. It demonstrated the potential effectiveness of this hybrid method for assessing vibration transmission into structures atop existing railway tracks. By integrating field measurements, finite element simulations, and analytical impedance models, the proposed hybrid method provides a framework for evaluating the transmission of the train-induced vibration to nearby building structures. Full article

On-demand urban delivery increasingly relies on electric delivery bicycles (EDBs), yet their limited battery capacity creates coupled challenges of routing efficiency and energy replenishment. We study a novel battery swapping cabinet location-routing problem (BSC-LRP) with multiple depots, which jointly optimizes routing and modular energy infrastructure deployment under time-window and battery constraints. To address the problem’s complexity, we design an improved branch-and-price algorithm enhanced with adaptive heuristic-exact labeling (IBP-HL) and a robust arc-based branching scheme. This hybrid framework accelerates column generation while preserving exactness, representing a methodological advancement over standard B&P approaches. Computational experiments on modified Solomon instances show that IBP-HL consistently outperforms Gurobi in both runtime and solution quality on small cases, and achieves substantial speedups and improved bounds over baseline B&P on medium and large cases. These results demonstrate not only the scalability of IBP-HL but also its practical relevance: the framework provides decision support for operators and planners in designing cost-efficient, reliable, and sustainable last-mile delivery systems with battery-swapping infrastructure. Full article

As wind turbines are affected by the harsh marine environment, inspection is crucial for the continuous operation of offshore wind farms. Nowadays, the main method of inspection is manual inspection, which has significant limitations in terms of safety, economy, and labor. With the advancement of technology, unmanned inspection systems have attracted more attention from researchers and the industry. This study proposes a novel framework to enable Unmanned Aerial Vehicles (UAVs) to improve their adaptability in autonomous inspection tasks on offshore wind farms, which includes multi-UAVs, inspection task nodes, and multiple charging stations. The main contributions of this paper are as follows: we propose an improved PSO algorithm to improve the location of charging stations; based on the multi-depot traveling salesman problem, we establish a multi-station UAV cooperative task allocation model with energy constraints, with the inspection time consumption of UAVs as the optimization objective; we also propose the Dynamic elite Double population Genetic Algorithm (DDGA) to aid in the cooperative task allocation of UAVs. The simulation results show that, compared with other algorithms, the proposed framework has higher universality and superiority. This paper provides a specific method for the application of unmanned inspection systems in the inspection of wind turbines in offshore wind farms. Full article

Photovoltaic (PV) energy has become a pillar of clean energy in rural areas. However, its extensive deployment in regions with geographically dispersed locations and limited road conditions has made efficient inspection a significant challenge. To address these issues, this study proposes a multi-regional PV inspection path planning method based on the crested porcupine optimization (CPO) algorithm. This method first employs a hybrid optimization framework combining a genetic algorithm, Simulated Annealing, and Fuzzy C-Means Clustering (GASA-FCM) to divide PV power stations into multiple regions, adapting to their dispersed distribution characteristics. Subsequently, the CPO algorithm is used to calculate obstacle-avoidance paths, replacing the Euclidean distance in the traditional Traveling Salesman Problem (TSP) with adaptive rural road constraint conditions to better cope with the geographical complexity in real-world scenarios. The simulation results verify the advantages of this method, achieving significantly shorter path lengths, higher computational efficiency, and stronger stability compared to the traditional solutions, thereby improving the efficiency of rural PV inspection. Moreover, the proposed framework not only provides a practical inspection strategy for rural PV systems but also offers a solution to the Multiple-Depot Multiple Traveling Salesmen Problem (MDMTSP) under constrained conditions, expanding its application scope in similar scenarios. Full article

Epicardial adipose tissue (EAT) is a unique fat depot located around the heart, intimately associated with the myocardium and coronary arteries. The secretion of bioactive molecules and their interaction with neighbouring cardiac tissues makes it an active organ with important implications in cardiovascular health and disease. In recent years, omics technologies have provided valuable insights into the molecular characteristics and functional relevance of EAT in patients with coronary atherosclerosis, myocardial infarction, atrial fibrillation and associated metabolic disorders. This review aims to summarize the current understanding of EAT biology through the lens of genomics, transcriptomics, proteomics and lipidomics approaches. We discuss key findings from omics studies on EAT, including gene expression profiles, metabolic activity, signalling pathways and regulatory network, in order to explore in depth the disease mechanisms, possible therapeutic strategies, and cardiovascular risk assessment. Further advances in this field and integrating data from multiple omics platforms hold promise for unlocking personalized cardiometabolic profiles with EAT as a possible biomarker and therapeutic target in cardiovascular disease. Full article

As more and more cities try to reduce their CO₂ emissions, public transport fleets are undergoing a transition from conventional to electric vehicles. To complete this shift, there is a need to build the required charging infrastructure. When the first electric buses were adopted, the charging stations were mostly built in the locations of large bus depots. However, in recent years, there has been a crowding problem in the charging stations resulting in queuing and unnecessary delays. In this study, we explore the potential of replacing single-port charging stations with multi-port charging stations that can serve multiple vehicles at once with a reduced charging rate. Because the charging rate reduces with the number of ports, we develop a mixed-integer linear program to determine the charging schedules of bus fleets in order to reduce the overall delays in the bus network. The novel formulation is tested in benchmark instances of various sizes demonstrating the improvement potential. Full article

Pericytes (PCs) are located surrounding the walls of small blood vessels, particularly capillaries and microvessels. In addition to their functions in maintaining vascular integrity, participating in angiogenesis, and regulating blood flow, PCs also serve as a reservoir for multi-potent stem/progenitor cells in white, brown, beige, and bone marrow adipose tissues. Due to the complex nature of this cell population, the identification and characterization of PCs has been challenging. A comprehensive understanding of the heterogeneity of PCs may enhance their potential as therapeutic targets for metabolic syndromes or bone-related diseases. This mini-review summarizes multiple PC markers commonly employed in lineage-tracing studies, with an emphasis on their contribution to adipogenesis and functions in different adipose depots under diverse metabolic conditions. Full article

In this study, we present a mathematical model and solution approach for addressing the robust integrated intercity railway depot location and line planning problem (RIDLLPP), which encompasses the initial two stages of the railway planning process. Our primary objective is to identify depot locations that exhibit robustness across a range of likely future scenarios, and this is achieved by incorporating line planning decisions. The model focuses on five critical strategic determinations, namely the depot location, depot storage capacity, line operation, passenger assignment, and fleet allocation. To tackle this complex problem, we propose an iterative solution framework that combines the Differential Evolution (DE) algorithm with improved rounding heuristics (DE-IRH). To evaluate the effectiveness of our framework, we conduct a comparative analysis with the Gurobi solver using multiple medium-sized artificial instances. The results demonstrate that our proposed framework achieves an optimality gap of 4.87% while requiring less computational time. Furthermore, we validate the robustness of the model’s location choices across various input scenarios, thereby providing valuable insights for transportation planning agencies and railway companies that can inform their decision-making processes. Full article

Fat deposition is a significant economic trait in livestock animals. Adipose tissues (ATs) developed in subcutaneous and visceral depots are considered waste whereas those within muscle are highly valued. In river buffaloes, lipogenesis is highly active in subcutaneous (especially in the sternum subcutaneous) and visceral depots but not in muscle tissue. Revealing the features and functions of ATs in different depots is significant for the regulation of their development. Here, we characterize the cell size, composition, and function of six AT depots in river buffaloes. Our data support that the subcutaneous AT depots have a larger cell size than visceral AT depots, and the subcutaneous AT depots, especially the sternum subcutaneous AT, are mainly associated with the extracellular matrix whereas the visceral AT depots are mainly associated with immunity. We found that sternum subcutaneous AT is significantly different from ATs in other depots, due to the high unsaturated fatty acid content and the significant association with metabolic protection. The perirenal AT is more active in FA oxidation for energy supply. In addition, the expression of HOX paralogs supports the variable origins of ATs in different depots, indicating that the development of ATs in different depots is mediated by their progenitor cells. The present study enhances our understanding of the cellular and molecular features, metabolism, and origin of AT depots in buffaloes, which is significant for the regulation of fat deposition and provides new insights into the features of AT depots in multiple discrete locations. Full article

Adipose tissue and its diverse cell types constitute one of the largest endocrine organs. With multiple depot locations, adipose tissue plays an important regulatory role through paracrine and endocrine communication, particularly through the secretion of a wide range of bioactive molecules, such as nucleic acids, proteins, lipids or adipocytokines. Over the past several years, research has uncovered a myriad of interorgan communication signals mediated by small lipid-derived nanovesicles known as extracellular vesicles (EVs), in which secreted bioactive molecules are stably transported as cargo molecules and delivered to adjacent cells or remote organs. EVs constitute an essential part of the human adipose secretome, and there is a growing body of evidence showing the crucial implications of adipose-derived EVs in the regulation of heart function and its adaptative capacity. The adipose tissue modifications and dysfunction observed in obesity and aging tremendously affect the adipose-EV secretome, with important consequences for the myocardium. The present review presents a comprehensive analysis of the findings in this novel area of research, reports the key roles played by adipose-derived EVs in interorgan cross-talk with the heart and discusses their implications in physiological and pathological conditions affecting adipose tissue and/or the heart (pressure overload, ischemia, diabetic cardiomyopathy, etc.). Full article

In this paper, we propose a solution for optimizing the routes of Mobile Medical Units (MMUs) in the domain of vehicle routing and scheduling. The generic objective is to optimize the distance traveled by the MMUs as well as optimizing the associated cost. These MMUs are located at a central depot. The idea is to provide improved healthcare to the rural people of India. The solution is obtained in two stages: preparing a mathematical model with the most suitable parameters, and then in the second phase, implementing an algorithm to obtain an optimized solution. The solution is focused on multiple parameters, including the number of vans, number of specialists, total distance, total travel time, and others. The solution is further supported by Reinforcement Learning, explaining the best possible optimized route and total distance traveled. Full article

Obesity with its associated complications represents a social, economic and health problem of utmost importance worldwide. Specifically, obese patients carry a significantly higher risk of developing cardiovascular disease compared to nonobese individuals. Multiple molecular mechanisms contribute to the impaired biological activity of the distinct adipose tissue depots in obesity, including secretion of proinflammatory mediators and reactive oxygen species, ultimately leading to an unfavorable impact on the cardiovascular system. This review summarizes data relating to the contribution of the main adipose tissue depots, including both remote (i.e., intra-abdominal, hepatic, skeletal, pancreatic, renal, and mesenteric adipose fat), and cardiac (i.e., the epicardial fat) adipose locations, on the cardiovascular system. Finally, we discuss both pharmacological and non-pharmacological strategies aimed at reducing cardiovascular risk through acting on adipose tissues, with particular attention to the epicardial fat. Full article